File size: 1,837 Bytes
17ead0c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | import math
import random
import numpy as np
from PIL import Image
from core.base import GradientStyle
from core import color_utils
def _hex_to_rgb(hex_color: str) -> tuple[int, int, int]:
h = hex_color.lstrip("#")
return tuple(int(h[i:i+2], 16) for i in (0, 2, 4))
def _to_linear(v: np.ndarray) -> np.ndarray:
"""sRGB → linear light (gamma decode)."""
v = v / 255.0
return np.where(v <= 0.04045, v / 12.92, ((v + 0.055) / 1.055) ** 2.4)
def _to_srgb(v: np.ndarray) -> np.ndarray:
"""Linear light → sRGB (gamma encode)."""
return np.where(v <= 0.0031308, v * 12.92, 1.055 * v ** (1.0 / 2.4) - 0.055)
class LinearGradient(GradientStyle):
def __init__(self, width: int, height: int, colors: list[str], angle: float = 0.0):
super().__init__(width, height)
self.colors = colors
self.angle = angle
def render(self) -> Image.Image:
rad = math.radians(self.angle)
cos_a, sin_a = math.cos(rad), math.sin(rad)
ys, xs = np.mgrid[0:self.height, 0:self.width]
cx, cy = self.width / 2, self.height / 2
proj = (xs - cx) * cos_a + (ys - cy) * sin_a
proj -= proj.min()
denom = proj.max()
t = (proj / denom if denom != 0 else proj).astype(np.float32)
c0 = _to_linear(np.array(_hex_to_rgb(self.colors[0]), dtype=np.float32))
c1 = _to_linear(np.array(_hex_to_rgb(self.colors[1]), dtype=np.float32))
blended_lin = c0 * (1 - t[..., None]) + c1 * t[..., None]
img_arr = np.clip(_to_srgb(blended_lin) * 255, 0, 255).astype(np.uint8)
return Image.fromarray(img_arr, "RGB")
def random_params(width: int, height: int, rng: random.Random) -> dict:
return {
"colors": color_utils.random_palette(rng, 2, scheme="complementary"),
"angle": rng.uniform(0, 360),
}
|